Image Processing - 2023.2 English

The following steps demonstrate the Image Processing procedure in the hardware pipeline

1. xf::cv::cornerharris is called to start processing the first input image
2. The output ofxf::cv::cornerHarris is fed toxf::cv::cornersImgToList. This function takes in an image with corners (marked as 255 and 0 elsewhere), and converts them to a list of corners.
3. xf::cv::pyrDown creates the two image pyramids and Dense Optical Flow is computed using the two image pyramids as described in the Iterative Pyramidal Dense Optical Flow example.
4. xf::cv::densePyrOpticalFlow is called with the two image pyramids as inputs.
5. xf::cv::cornerUpdate function is called to track the corner locations in the second image. If harris_flag is enabled, the cornerUpdate tracks corners from the output of the list, else it tracks the previously tracked corners.

The HarrisImg() function takes a flag called harris_flag which is set during the first frame or when the corners need to be redetected. The xf::cv::cornerUpdate function outputs the updated corners to the same memory location as the output corners list of xf::cv::cornerImgToList. This means that when harris_flag is unset, the corners input to the xf::cv::cornerUpdate are the corners tracked in the previous cycle, that is, the corners in the first frame of the current input frames.

After the Dense Optical Flow is computed, if harris_flag is set, the number of corners that xf::cv::cornerharris has detected and xf::cv::cornersImgToList has updated is copied to num_corners variable . The other being the tracked corners list, listfixed. If harris_flag is set, xf::cv::cornerUpdate tracks the corners in ‘list’ memory location, otherwise it tracks the corners in ‘listfixed’ memory location.